Method and device for tracing the motion of blood vessel boundaries

ABSTRACT

Embodiments of the present disclosure are directed to an vascular-dynamics-monitoring device (100) and methods for tracing a motion of boundaries of a vessel in a human body. The method features an automated gating of vessel walls&#39; echoes in an ultrasound frame input to the vessel, accurate shift estimation for the gated vessel wall region, despite the presence of echoes from moving structures adjacent to the vessel and real-time trace of vessel walls&#39; boundaries.

PRIORITY DETAILS

The present application is based on, and claims priority fromInternational Application PCT/IN2021/050412 filed 27 Apr. 2021 andIndian Application Number 202041017855 filed on 27 Apr. 2020, thedisclosures of which are hereby incorporated by reference herein.

TECHNICAL FIELD

The present disclosure relates to medical monitoring and analysis, andmore particularly to tracing motion of blood vessel boundaries.

BACKGROUND

Arterial lumen diameter and wall thickness (assessed as intima-mediathickness) constitute important sub-clinical measurements ofcardiovascular risks. Several multicentre clinical studies and meta-dataanalyses have provided outcomes that recommend these measures asestablished surrogates and independent markers of various cardiovascularevents, pathologies, and disease progression. Simultaneous measurementof their instantaneous values can help furnish several functional andmaterial properties of the blood vessels. These properties include thedistensibility (or compliance), stiffness index, modulus of elasticity,local pulse wave velocity and its variation within a cardiac cycle,viscoelasticity, wall-buffering function, endothelial dysfunction,central blood pressure, etc.

The non-invasive measurement of arterial diameter or wall thickness andtheir changes is performed using imaging technologies traditionally.This involves two tasks, the first of which is a localization oridentification of vessel wall echoes which is a high-level task and thesecond is tracking those locations over time in each new scan. Thesetask of manually inspecting each scanned frame and tracking the boundarylocations is tedious and time consuming, and thereby need furtherattention.

While a method's accuracy is implicit, it is desirable if themeasurements are yielded real-time and in automated or semi-automatedfashion. Such methods that depend minimally on the operator are likelyto reduce the time consumed for the measurement procedure and contributetowards better repeatability. This is particularly important toaccelerate large scale studies or field-level screening, and also insettings with resource-constraints. Recent works have reviewed severalautomated and semi-automated techniques that employ segmentation onB-mode ultrasound images to evaluate the diameter and wall thickness.These state-of-the-art B-mode techniques meet the necessary clinicalstandards and requirements concerning the measurement of the artery'sdimensional parameters. However, these modalities are expensive, and theadvanced features required for performing such measurements are notaugmented to the entry-level devices. Additionally, they arenon-scalable, demand a skilled operator, and do not cater toout-of-clinic applications. In the context of India, the legalconstraints imposed by the Pre-Natal Diagnostic Techniques (PNDT) actrestrict imaging ultrasound devices to be deployed to field, unlessotherwise with special approvals. This has affected the readyavailability of these ultrasound technologies to the rural sector ofIndia where the resources are scarce, both in terms of man-power andmachinery.

Measurement of change in diameter is done based on determining a motionof vessel boundaries in addition to determining the boundary walls.There remains a need to provide for accurate determinations of themotion of vessel boundaries.

In light of the above, there is a need to overcome the above stateddisadvantages.

SUMMARY

Embodiments of the present disclosure are directed to a system andmethods for tracing a motion of a vessel in a human body. The methodfeatures an automated gating of vessel walls' echoes in an ultrasoundframe input to the vessel, accurate shift estimation for the gatedvessel wall region, despite the presence of echoes from movingstructures adjacent to the vessel and real-time trace of vessel walls'boundaries.

Embodiments of the present disclosure are directed to a method fortracing motion of blood vessel boundaries in a human body. The methodincludes receiving, by an vascular-dynamics-monitoring device, aplurality of ultrasound signals from the blood vessel, continuouslyextracting, by the vascular-dynamics-monitoring device, at least twoconsecutive ultrasound frames from the plurality of ultrasound signalsreceived, identifying, by an vascular-dynamics-monitoring device,locations of a proximal wall and a distal wall of the blood vessel basedon the at least two consecutive ultrasound frames by the,vascular-dynamics-monitoring device; dynamically extracting, by thevascular-dynamics-monitoring device, at least one echo region ofproximal wall and at least one echo region of distal wall from each ofthe at least two ultrasound frames based on the identified locations ofthe proximal wall and distal wall of the blood vessel, comparing, by thevascular-dynamics-monitoring device, the at least one echo region ofproximal wall and at least one echo region of distal wall from each ofthe at least two consecutive ultrasound frames to determine at least onedelay waveform between the each of the regions or first time-derivativeof unwrapped analytic phase waveforms of the each of the proximal wallecho region and the distal wall region of each of the at least twoconsecutive ultrasound frames, continuously determining, by thevascular-dynamics-monitoring device, at least one extremum of the delaywaveform or at least two extrema of interest of the firsttime-derivative of the unwrapped analytic phase waveforms, wherein theat least one extremum of the delay waveform or the average shift in theat least two extrema of interest of the first time-derivative of theunwrapped analytic phase waveforms is indicative of a shift of the atleast one echo region on each of the proximal wall and the distal wall,and tracing, by the vascular-dynamics-monitoring device, the motion ofthe proximal wall and the distal wall based on the continuouslydetermined motion shift of the at least one echo region on each of theproximal wall and the distal wall.

Another embodiment of the present disclosure is directed to continuingtracing of the proximal wall and the distal wall until the tracingconcurs with an expected motion of the proximal wall and the distalwall.

Another embodiment of the present disclosure is directed to anultrasound frame being a digitized data frame of the ultrasound echosignal with a finite number of samples.

Another embodiment of the present disclosure is directed to the proximalwall and the distal wall of the blood vessel of the subject moving inopposite directions.

Another embodiment of the present disclosure is directed to whereindynamically identifying at least one echo region on each of the proximalwall and the distal wall comprises placing at least two windows withdynamically allocated sizes around each of the plurality of ultrasoundsignals received from the identified proximal wall and the identifieddistal wall.

Another embodiment of the present disclosure is directed to comparingsamples of the at least one echo region of each of the proximal wall andthe distal wall of each of the at least two consecutive ultrasoundframes to determine a delay waveform between the corresponding echoregions of the at least two consecutive ultrasound frames comprisescomparing samples of the echo regions to determine an alignmentdissimilarity between the echo regions, generating a two dimensionalalignment error matrix based on the alignment dissimilarity between theecho regions, translating the two dimensional error matrix to anaccumulated distance matrix, determining local minimum accumulatederrors and global minimum accumulated errors from the accumulateddistance matrix, and generating the delay waveform based on thedetermined local minimum accumulated errors and the global minimumaccumulated errors.

Another embodiment of the present disclosure is directed to processingsamples of the at least one echo region of each of the proximal wall andthe distal wall of each of the at least two consecutive ultrasoundframes to determine a first derivative of unwrapped phase changewaveform between the at least two consecutive ultrasound framescomprises determining a quadrature phase counterpart corresponding toeach of the at least one echo region of each of the at least twoultrasound frames by applying Hilbert transform on the each of the atleast two ultrasound frames, generating a single sideband (SSB) signalcorresponding to each of the at least one echo region of each of the atleast two ultrasound frames by adding the each of the echo regions tothe corresponding quadrature phase counterpart, constructing continuousphase waveforms of each of the echo regions by performing a tangentinverse operation on the SSB signal corresponding to each of the atleast two ultrasound frames, constructing the unwrapped phase waveformsby performing a time-domain unwrapping operation, differentiating theunwrapped phase waveforms of each of the at least one echo region ofeach of the proximal wall and the distal wall with respect to time once.

Another embodiment of the present disclosure is directed to the echoregions including an equal number of samples.

Another embodiment of the present disclosure is directed to the echoregions including an unequal number of samples.

Embodiments of the present disclosure are directed tovascular-dynamics-monitoring device for identifying boundaries of ablood vessel in a human body. The vascular-dynamics-monitoring deviceincludes a memory storing ultrasound frames, a signal transceiverconfigured for receiving a plurality of ultrasound echo signals from aproximal wall and a distal wall of the blood vessel, a sample extractorand a controller that is communicatively connected to the sampleextractor, the signal transceiver and the memory. The sample extractoris configured for continuously extracting at least two consecutiveultrasound frames from the plurality of ultrasound echo signals receivedfrom the at least one echo region, dynamically extracting at least oneecho region from each of the at least two ultrasound frames, and storingthe at least two consecutive ultrasound frames in the memory. Thecontroller is configured for comparing, by thevascular-dynamics-monitoring device, the at least one echo region fromeach of the at least two consecutive ultrasound frames to determine atleast one delay waveform between the each of the regions or firsttime-derivative of unwrapped analytic phase waveforms of the each of theproximal wall echo region and the distal wall region of each of the atleast two consecutive ultrasound frames, continuously determining, bythe vascular-dynamics-monitoring device, at least one extremum of thedelay waveform or at least two extrema of interest of the firsttime-derivative of the Unwrapped analytic phase waveforms, wherein theat least one extremum of the delay waveform or the average shift in theat least two extrema of interest of the first time-derivative of theunwrapped analytic phase waveforms is indicative of a shift of the atleast one echo region on each of the proximal wall and the distal wall,and tracing, by the vascular-dynamics-monitoring device, the motion ofthe proximal wall and the distal wall based on the continuouslydetermined motion shift of the at least one echo region on each of theproximal wall and the distal wall.

BRIEF DESCRIPTION OF FIGURES

Having thus described the disclosure in general terms, reference willnow be made to the accompanying figures, wherein:

FIG. 1 illustrates a vascular-dynamics-monitoring device for tracingmotion of boundaries of a vessel in a body, in accordance with variousembodiments of the present disclosure;

FIG. 2 is flow diagram illustrating a time domain method for tracingmotion of boundaries of a vessel in a human body, in accordance withvarious embodiments of the present disclosure;

FIG. 3 is a flow diagram illustrating a frequency domain method fortracing motion of boundaries of a vessel in the human body, inaccordance with various embodiments of the present disclosure.

FIG. 4 is a flow diagram, illustrating the primary stages of the methodfor tracing motion of the boundaries of the vessel in the body, inaccordance with various embodiments of the present disclosure;

FIG. 5 is a set of intermediate-stage signal graph illustrating the timedomain method to trace motion of boundaries of a vessel in the humanbody using the vascular-dynamics-monitoring device, in accordance withvarious embodiments of the present disclosure; and

FIG. 6 is a set of intermediate-stage signal graph illustrates thefrequency domain method to trace motion of boundaries of a vessel in abody using the vascular-dynamics-monitoring device, in accordance withvarious embodiments of the present disclosure.

It should be noted that the accompanying figures are intended to presentillustrations of exemplary embodiments of the present disclosure. Thesefigures are not intended to limit the scope of the present disclosure.It should also be noted that accompanying figures are not necessarilydrawn to scale.

DETAILED DESCRIPTION OF EMBODIMENT

Various embodiments of the present disclosure will now be described indetail with reference to the accompanying drawings. In the followingdescription, specific details such as detailed configuration andcomponents are merely provided to assist the overall understanding ofthese embodiments of the present disclosure. Therefore, it should beapparent to those skilled in the art that various changes andmodifications of the embodiments described herein can be made withoutdeparting from the scope and spirit of the present disclosure. Inaddition, descriptions of well-known functions and constructions areomitted for clarity and conciseness.

Also, the various embodiments described herein are not necessarilymutually exclusive, as some embodiments can be combined with one or moreother embodiments to form new embodiments. Herein, the term “or” as usedherein, refers to a non-exclusive or, unless otherwise indicated. Theexamples used herein are intended merely to facilitate an understandingof ways in which the embodiments herein can be practiced and to furtherenable those skilled in the art to practice the embodiments herein.Accordingly, the examples should not be construed as limiting the scopeof the embodiments herein. Further it should be possible to combine theflows specified in different figures to derive a new flow.

As is traditional in the field, embodiments may be described andillustrated in terms of blocks which carry out a described function orfunctions. These blocks, which may be referred to herein as managers,engines, controllers, units or modules or the like, are physicallyimplemented by analog and/or digital circuits such as logic gates,integrated circuits, microprocessors, microcontrollers, memory circuits,passive electronic components, active electronic components, opticalcomponents, hardwired circuits and the like, and may optionally bedriven by firmware and software. The circuits may, for example, beembodied in one or more semiconductor chips, or on substrate supportssuch as printed circuit boards and the like. The circuits constituting ablock may be implemented by dedicated hardware, or by a processor (e.g.,one or more programmed microprocessors and associated circuitry), or bya combination of dedicated hardware to perform some functions of theblock and a processor to perform other functions of the block. Eachblock of the embodiments may be physically separated into two or moreinteracting and discrete blocks without departing from the scope of thedisclosure. Likewise, the blocks of the embodiments may be physicallycombined into more complex blocks without departing from the scope ofthe disclosure.

The embodiments herein and the various features and advantageous detailsthereof are explained more fully with reference to the non-limitingembodiments that are illustrated in the accompanying drawings anddetailed in the following description.

The embodiments disclosed herein can be implemented through at least onesoftware program running on at least one hardware device and performingnetwork management functions to control the elements. The elements shownin FIGS. 1-6 include blocks which can be at least one of a hardwaredevice, or a combination of hardware device and software module.

In accordance with embodiments disclosed herein, document managementinvolves acquiring any document and then retrieving document propertiesto map them to a pre-stored set of documents. Depending upon thedocument category, relevance of data inside document in any form such astext, QR code, etc. can be determined for providing services to thesubject.

Reference in this specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the present technology. The appearance of the phrase “in oneembodiment” in various places in the specification are not necessarilyall referring to the same embodiment, nor are separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, variousfeatures are described which may be exhibited by some embodiments andnot by others. Similarly, various requirements are described, which maybe requirements for some embodiments but no other embodiments.

Moreover, although the following description contains many specifics forthe purposes of illustration, anyone skilled in the art will appreciatethat many variations and/or alterations to said details are within thescope of the present technology. Similarly, although many of thefeatures of the present technology are described in terms of each other,or in conjunction with each other, one skilled in the art willappreciate that many of these features can be provided independently ofother features. Accordingly, this description of the present technologyis set forth without any loss of generality to, and without imposinglimitations upon, the present technology.

FIG. 1 illustrates a vascular-dynamics-monitoring device 100 for tracingthe motion of a blood vessel. The vascular-dynamics-monitoring device100 includes a memory 102, a signal transceiver 104, a sample extractor106 and an ultrasound transducer 110 and a controller 108. Theultrasound transducer 110 may include an inbuilt (or external)transmitter and a receiver that transmit and receive ultrasound signals.While the generated ultrasound signal of the ultrasound transducer 110propagates through a target site on a body, several ultrasound echoesare generated from various structures in the transmission path. Theseechoes are captured by the signal transceiver 104 and is converted intosignature analog waves using an analog signal generator 106B of thesample extractor 106. These analog signals are then processed withvarious signal conditioning elements, as desired using the framegenerator 106C. These conditioned ultrasound analog signals areconverted into digital signals using an analog to digital converter 106Aand are stored temporarily in the memory 102. It is a continuous processand is controlled by the controller 108. The digitised ultrasound echosignals are transferred to a digital domain for further analyses and toperform various measurements by implementing aforesaid methods. Of note,an echo signal with a finite number of samples in the digital domainhenceforth referred to as an ultrasound frame.

The ultrasound frames, acquired via the sample extractor 106, containechoes formed from various tissue interfaces along the axis of theultrasound scan. If the target artery vessel is situated along the scanline, the echoes formed from the boundaries of the artery appear to beshifting in each consecutive frame with a characteristic pattern.Typically, in the case of arteries, such boundaries can be named asproximal wall and distal wall of the artery. The proximal and distalwalls would be moving in a direction opposite to each other. In thefollowing paragraphs, two systematic methods, a time domain method and afrequency domain method, are described to locate and identify boundariesof the artery (viz. proximal wall and distal wall of the artery) byanalysing the acquired ultrasound echo frames. It should be noted that,although the following method described in the context of an artery, isdirectly applicable to any vascular structure encompassing fluid with acharacteristic motion.

In some embodiments, the vascular-dynamics-monitoring device 100 mayinclude communication units pertaining to communication with remotecomputers, servers or remote databases over a communication network. Thecommunication network can include a data network such as, but notrestricted to, the Internet, local area network (LAN), wide area network(WAN), metropolitan area network (MAN) etc. In certain embodiments, thecommunication network can include a wireless network, such as, but notrestricted to, a cellular network and may employ various technologiesincluding enhanced data rates for global evolution (EDGE), generalpacket radio service (GPRS), global system for mobile communications(GSM), Internet protocol multimedia subsystem (IMS), universal mobiletelecommunications system (UMTS) etc.

The controller 108 can be, but not restricted to, a Central ProcessingUnit (CPU), a microprocessor, or a microcontroller. The controller 108executes sets of instructions stored on the memory 102.

The memory 102 includes storage locations to be addressable through thecontroller 108. The memory 102 is not limited to a volatile memoryand/or a non-volatile memory. Further, the memory 102 can include one ormore computer-readable storage media. The memory 102 can includenon-volatile storage elements. For example, non-volatile storageelements can include magnetic hard discs, optical discs, floppy discs,flash memories, or forms of electrically programmable memories (EPROM)or electrically erasable and programmable (EEPROM) memories. In someembodiments, the memory 102 is communicably coupled to third partystorage, cloud storage and the like.

The ultrasound frames acquired via the signal transceiver (104) containechoes formed from various tissue interfaces along the axis of theultrasound scan. If the target artery vessel is situated along the scanline, the echoes formed from the boundaries of the artery appear to beshifting in each consecutive frame with a characteristic pattern.Typically, in the case of arteries, such boundaries can be named asproximal wall and distal wall of the artery. The proximal and distalwalls would be moving in a direction opposite to each other. In thefollowing paragraphs, a systematic method is described to locate andidentify boundaries of the artery (viz. proximal wall and distal wall ofthe artery) by analysing the acquired ultrasound echo frames. It shouldbe noted that, although the following method described in the context ofan artery, is directly applicable to any vascular structure encompassingfluid with a characteristic motion.

FIG. 2 illustrates a time domain method (200) for tracing motion ofboundaries of a vessel in the human body, in accordance with variousembodiments of the present disclosure. In the method disclosed herein,as described in FIG. 2 , continuous tracing of a dynamic location andmotion pattern of the vessel boundaries is described. It is achieved byanalysing a relative motion of the identified boundaries across thecontinuous ultrasound frames. Although the following sections aredescribed in the context of an arterial vessel and tracing its proximaland distal walls, the method is directly applicable to any vascularstructure encompassing fluid with a characteristic motion.

Once approximate locations of vessel boundaries are identified with asuitable manual or automated method, the approximate locations of vesselboundaries act as the initial locations of the proximal and distal walls(step 238). Two windows of sufficient and equal size (dynamicallyallocated) are placed around the echoes originated from the proximal anddistal wall boundaries (step 201 and step 202). The centre portion ofthe said windows are placed, however not constrained, at the previouslyidentified boundary locations. Such extracted subsets from F^(th) and(F−1)^(th) frames are then analysed.

The alignment dissimilarity between the extracted proximal wall's subsetof F^(th) and (F−1)^(th) frames is measured by generating an errormatrix E(k,n).

In an embodiment, ultrasound frames are continuously collected andstored in a buffer. Two consecutive frames, the current frame F and itsprevious frame (F−1) are used at a time. Typically, both F^(th) and(F−1)^(th) frame have an equal number of samples (N), else are madeequal. From these the proximal and the distal wall subsets areextracted. Then the alignment dissimilarity between these frames'subsets is measured by generating an error matrix. Since two consecutiveframes are used, the error matrix will be a two-dimensional matrix. Thesame operation can be performed with any desired number of successiveframes, which would result in an error matrix with the correspondingdimensionality (step 204).

Any n^(th) column in the two-dimensional error matrix E(k,n) ispopulated by comparing a sample at index n in F^(th) frame subset, with(2K+1) samples in (F−1)^(th) frame subset, extracted using a window withits centre at the n^(th) index of the frame (F−1) subset. It can becompared in any form such as, but not limited to, algebraic or logical.For example, the samples are compared using an ‘absolute differenceoperator’ in Equation (1) and the description that follows. Thiscomparison operation is performed for all the samples in the F^(th)frame subset (S₁ signal) by correspondingly shifting the window centrein the (F−1)^(th) frame subset (S₂ signal). Subsequently, there are Ncolumns in error matrix E(k,n) with each column consisting of (2K+1)samples. Here, k represents the lags from the selected windows' centreindex in (F−1)^(th) frame subset from which the samples are extractedfor comparison against one sample extracted from the F^(th) framesubset. In each column of E(k,n) the indices of minima represent thelags that align the samples in F^(th) frame subset with the samples in(F−1)^(th) frame subset.

E(k,n)=|S ₁(n)−S ₂(n−k)|;n=[1,N] and k=[−K,K]  (1)

Once the error matrix E(k,n) is derived, it is translated to an‘accumulated error matrix’ D(k,n) as a representation of the cumulativeerrors while traversing across the length of the frame via a various lagpath (step 206). However not constrained to, the first column of D(k,n)is initialized as the first column of E(k,n) as:

D(k,1)=E(k,1).  (2)

From the second column to the N^(th), elements of D(k,n) in a k^(th) rowand n^(th) column are obtained by adding the element in E(k,n)corresponding to the k^(th) row and n^(th) column with the smallest ofthe elements extracted from (k−1)^(th), k^(th) and (k+1)^(th) rows inthe (n−1)^(th) column, as shown in Equation (3);

$\begin{matrix}{{D\left( {k,n} \right)} = {{E\left( {k,n} \right)} + {\min\left\{ \begin{matrix}{D\left( {{k - 1},{n - 1}} \right)} \\{{D\left( {k,{n - 1}} \right)},{n = 2},3,{\ldots\ N}} \\{D\left( {{k + 1},{n - l}} \right.}\end{matrix} \right.}}} & (3)\end{matrix}$

This form of generating accumulated error matrix process iterativelyadds the minimum of the adjoining elements presents one column apart.Now the ‘local minimum accumulated errors’ are computed by traversing inthe reverse direction, that is from N^(th) column to Pt column ofD(k,n).

These accumulated error matrices are used to derive the delay waveformL(n), in the form of lags that best align the consecutive frame signals,for the proximal and distal wall echo regions. The procedure ofconstruction of L(n) involves, however not constrained, initialising thelag corresponding to the minimum of the last column elements in D(k,n)as L(N);

L(N)=arg(min D(k,N)),∀k.  (4)

The other elements of the matrix L(n) are to be estimated for n=N−1to 1. For this, the elements from any column n corresponding to lagsL(n+1)−1, L(n+1) and L(n+1)+1 are collected, and the lag correspondingto the minimum of these elements is assigned to L(n), as give below.

L(n)=arg(min D(k,n)), for, kϵ[L(n+1)+1,L(n+1),L(n+1)−1] and n=N−1,N−2, .. . 1  (5)

Therefore, the sub-paths yielding local minimum accumulated errors (step208) when sequentially connected, it constructs the complete pathestimating L(n) and producing a ‘global minimum accumulated error’ (step210).

For more robust evaluation of delay waveform L(n), a modified D(k,n)matrix construction can also be adopted. In this approach, instead ofconstructing D(k,n) for all the columns (n=1: N), it is constructed forcolumns that are spaced m positions apart. Therefore, the constructedaccumulated error matrix′ D(k,i), where i=1: m: N, consists of only N/mcolumns. Here, the first column of D(k,i) is initialised as the firstcolumn of E(k,n). Further, for the columns (i=2: N/m), any element ofD(k,i) in row k and column i is evaluated by first identifying (2m+1)paths that connect the element of E(k,n) in row k and column i*m to theelements in column (i−1)*m and rows (k−m): (k+m). These elements inE(k,n) along the individual paths are added to obtain (2m+1) such pathsummations and the minimum of these summation values corresponding to aparticular path is added to the element of E(k,n) in the k^(th) row and(i*m)^(th) column. This value is assigned to the element of D(k,i) inthe k^(th) row and i^(th) column.

Now once the delay waveforms are generated as alluded above (step 212),for both the proximal and distal wall region, the extrema of theirrespective delay waveforms are identified and labelled (step 214).Extrema of the delay waveform represent the shifts of the proximal anddistal subset echoes from (F−1)^(th) to F^(th) frame. The shifts ofproximal and distal walls corresponding to the F^(th) frame are added totheir accumulated shifts (resultant shift till (F−1)^(th) frame) (step216). Note that, if the tracing has just started, this previouslyaccumulated shift can be set to a predefined value (typicallyinitialized with zero). This procedure, therefore, continuously tracesthe shifts in the echoes of the selected region with every new incomingframe. The exact locations of the vessel wall boundaries in the currentframe are computed by adding the current accumulated shifts with theinitially identified wall locations (step 220 and step 222). These exactlocations further assist in shifting of the window centre that extractsthe proximal and distal wall regions in the consecutive frames (step 226and step 228). The proximal wall and distal wall locations are bufferedfor sufficient samples (step 230), and the mutual motion pattern betweenthem is quantified (step 232). This motion pattern is inspected bycomparing the expected physiological characteristic motion pattern ofthe arterial walls (step 234). The tracing of the walls is continueduntil the inspected motion concurs with the expected characteristicmotion; otherwise, the locations of the walls are again freshlyidentified (step 238).

FIG. 3 illustrates an independent frequency domain method for tracingmotion of boundaries of a vessel in a human body, in accordance withvarious embodiments of the present disclosure. The locations of vesselwall boundaries (proximal and distal wall locations) identified via asuitable manual or automated method act as the initial referencelocations to trace the wall dynamics and motion (or vibrations) ofvessel walls. Initially, a window with the dynamically allocated size isused to extract the proximal and distal wall echo regions constituting asufficient number of samples (step 301 and step 302). Hilbert transformoperation is applied on these proximal and distal wall echo regions ofthe F^(th) and (F−1)^(th) frame which yields their respectivequadrature-phase counterpart. By adding the regions from the originalframes (F and (F−1)) with their quadrature versions, G and (G−1),respectively single-sideband (SSB) signals are generated (step 304A).Phase waveforms of these regions are now evaluated using the constructedsingle sideband (SSB) signals for the extracted regions by performing atangent inverse operation on the ratio of their real and imaginaryparts.

The obtained phase is now constrained to the principle values, i.e., πto π. Further, an unwrap operation is performed to the phase by addingmultiples of ±2π whenever a jump in phase is greater than π, so as tobring it to a magnitude smaller than π (step 306A). This unwrapped phaseis linear with a few breakpoints or knots in the linear trend,corresponding to the boundaries of echo arising from each tissueinterface along the ultrasound scan line. Identification of thelocations of these breakpoints is performed using a unidirectionalsignal f(t) derived from the first-time derivative of the unwrappedphase waveforms (step 308A). More specifically, the f(t) signal isobtained by subtracting the first-time derivative of the unwrapped phasewith its mean and then performing a modulus operation (step 310A). Thisprocedure delineates various echoes from different tissue interfaces inthe extracted regions of the proximal wall and the distal wall. Further,the locations of interest, such as the locations corresponding to thelumen-intima and media-adventitia, are identified.

The interfaces of lumen-intima and media-adventitia are located from thepool of all the identified echo boundaries of the extracted region, asfollows. Envelopes are first constructed for the proximal and distalwall region extracts using a suitable method (304B). One method is touse the SSB signals of the regions, where the envelope can be estimatedas the magnitude of the complex-valued elements. An over smoothenedversion of this envelope is obtained, and its peak is identified (step306B). The location of the obtained peak (L_(P)) for the respectiveregions represent the location at which maximum energy of the extractedregions are concentrated (step 308B). Further, the two strong echoesthat are present to either side of this peak are the echoes formed dueto lumen-intima and media-adventitia interfaces (step 310B). In the caseof a proximal wall, the echo on the right side of L_(P) is identified asthe echo originated from the intima layer, and the echo on the left sideof L_(P) as the echo originated from the adventitia layer. Similarly,for distal wall region, the echo immediately to the left of the L_(P) isidentified as the echo originated from the intima layer, and echo on theright side of L_(P) as the echo originated from the adventitia layer.

Amongst all the echo boundaries previously identified for the proximalwall region, the leading boundary location of the intima echo isdesignated as the lumen-intima interface (LI_(PROX)), and the trailingboundary of the adventitia echo is designated as the media-adventitiainterface (MA_(PROX)) Also, amongst all the echo boundaries previouslyidentified for the distal wall region, the leading boundary location ofthe intima echo is designated as the lumen-intima interface (LI_(DIS)),and the leading boundary of the adventitia echo is designated as themedia-adventitia interface (MA_(DIS)). These interfaces are identifiedfor the F^(th) and (F−1)^(th) frames (step 318). The difference in theLI_(PROX) from the two frames and in the MA_(PROX) from the two framesare averaged to yield the proximal wall shift. A similar approach isadopted to produce the distal wall shift (step 320).

Another robust approach for wall shift estimation is to find the ΔΦwaveform for the combined intima and adventitia echoes that wereidentified in the F^(th) and (F−1)^(th) frames for respective wallregions. Further, the shift in locations of the proximal and distal wallechoes in units of time (measured as difference in time of flight ofechoes in F^(th) and (F−1)^(th) frames) are estimated by translating theaverage of values in the ΔΦ waveform using the expression; shift (inseconds)=(average of elements in ΔΦ)/(2π frequency of transducer).

These shifts corresponding to the F^(th) frame are added to thepreviously accumulated shifts till (F−1)^(th) (step 324A and step 324B).If the tracing has just started, this previously accumulated shift isinitialised with zero. This procedure, therefore, traces the shifts inthe echoes continuously with every new incoming frame. The exactlocations of the wall in the current frame are computed by adding thecurrent accumulated shifts with the initially identified wall locations.These exact locations assist in shifting of the window centre thatextracts the proximal and distal wall regions in the consecutive frames(step 328A and step 328B). The difference between the traces ofaccumulated shifts in the proximal and distal walls provide distensiontrace. Likewise, the difference between the traces of exact locations ofthe proximal and distal walls in the frame produces the diameterwaveform. The proximal wall and distal wall locations are buffered forevery N sufficient samples (step 330), and the mutual motion patternbetween them is quantified (step 332). This motion pattern is inspectedby comparing the physiological characteristic motion pattern of thearterial walls (step 334). The tracing of the walls is continued untilthe inspected motion concurs with the expected characteristic motion(step 336). Otherwise, the locations of the walls are again freshlyidentified (step 338).

FIG. 4 is a flow diagram (400), illustrating the method of tracing themotion of the blood vessel in the human body, according to an embodimentas disclosed herein.

As seen in FIG. 4 , At 402, the method comprises receiving ultrasoundecho signals from the transducer by the vascular-dynamics-monitoringdevice (100) from different location of the blood vessel.

At 404, the method comprises continuously extracting, by thevascular-dynamics-monitoring device (100), at least two consecutiveultrasound frames from the ultrasound echo signals.

At (406), the method comprises identifying, by thevascular-dynamics-monitoring device (100), the proximal wall and adistal wall of the blood vessel from the at least two consecutiveultrasound frames from the plurality of ultrasound signals.

At (408), the method includes dynamically extracting, by thevascular-dynamics-monitoring device (100), at least one echo region ofthe proximal wall and the distal wall of the blood vessels.

At (410), the at least one echo region from each of the at least twoconsecutive ultrasound frames are compared to determine at least onedelay waveform between the each of the regions or first time-derivativeof unwrapped analytic phase waveforms of the each of the proximal wallecho region and the distal wall region. In an embodiment, samples of theeach echo regions of the proximal wall and the distal walls are comparedto determine an alignment dissimilarity between the echo regions. Thetwo-dimensional alignment error matrix is generated based on thealignment dissimilarity between the echo regions. The two-dimensionalerror matrix is translated to an accumulated distance matrix. Furtherthe local minimum accumulated errors and global minimum accumulatederrors are determined from the accumulated distance matrix. Finally, thedelay waveform is generated based on the determined local minimumaccumulated errors and the global minimum accumulated errors. In anotherembodiment, samples of the each echo regions of the proximal wall andthe distal walls are used to determine a quadrature phase counterpartcorresponding to each of the at least one echo region by applyingHilbert transform on the each of the at least two ultrasound frames andgenerate a single sideband (SSB) signal corresponding to each of the atleast one echo region. A tangent inverse operation was performed on theSSB signal corresponding to each of the at least one echo region bywhich the unwrapped phase waveforms were constructed and, differentiatedwith respect to time once.

At (412), the vascular-dynamics-monitoring device (100) determines theshift of the at least one echo region on each of the proximal wall andthe distal wall based on the comparison.

At (414), the vascular-dynamics-monitoring device (100), traces themotion of the proximal wall and the distal wall based on thecontinuously determined motion shift of the at least one echo region oneach of the proximal wall and the distal wall.

FIG. 5 is a set of intermediate-stage signal graphs 500 illustrating thetime domain method to trace motion of boundaries of a vessel in a bodyusing the vascular-dynamics-monitoring device 100, in accordance withvarious embodiments of the present disclosure. Approximate locations ofvessel boundaries act as the initial locations of the proximal anddistal walls. As shown in FIG. 5 , two windows of sufficient and equalsize (dynamically allocated) are placed around the echoes originatedfrom the proximal and distal wall boundaries. The centre portion of thesaid windows are placed, however not constrained, at the previouslyidentified boundary locations. Such extracted subsets from F^(th) and(F−1)^(th) frames are then analysed.

Ultrasound frames are continuously collected from the echo regions andstored in a buffer. Two consecutive frames, the current frame F and itsprevious frame (F−1) are used at a time. Typically, both F^(th) and(F−1)^(th) frame have an equal number of samples (N), else are madeequal. From these the proximal and the distal wall subsets areextracted. Then the alignment dissimilarity between these frames'subsets is measured by generating an error matrix E. Since twoconsecutive frames are used, the error matrix will be a two-dimensionalmatrix. The same operation can be performed with any desired number ofsuccessive frames, which would result in an error matrix with thecorresponding dimensionality

Once the error matrix E(k,n) is derived, it is translated to an‘accumulated error matrix’ D(k,n) as a representation of the cumulativeerrors while traversing across the length of the frame via a various lagpath as shown in FIG. 5 . This form of generating accumulated errormatrix process iteratively adds the minimum of the adjoining elementspresents one column apart. Now the ‘local minimum accumulated errors’are computed by traversing in the reverse direction, that is from N^(th)column to 1^(st) column of D(k,n).

These accumulated error matrices are used to derive the delay waveformL(n), in the form of lags that best align the consecutive frame signals,for the proximal and distal wall echo regions. Once the delay waveformsare generated as shown in FIG. 5 , for both the proximal and distal wallregion, the extrema of their respective delay waveforms are identifiedand labelled. Extrema of the delay waveform represent the shifts of theproximal and distal subset echoes from (F−1)^(th) to F^(th) frame. Theshifts of proximal and distal walls corresponding to the F^(th) frameare added to their accumulated shifts (resultant shift till (F−1)^(th)frame). If the tracing has just started, this previously accumulatedshift can be set to a predefined value (typically initialized withzero). This procedure, therefore, continuously traces the shifts in theechoes of the selected region with every new incoming frame. The exactlocations of the vessel wall boundaries in the current frame arecomputed by adding the current accumulated shifts with the initiallyidentified wall locations. These exact locations further assist inshifting of the window centre that extracts the proximal and distal wallregions in the consecutive frames. The proximal wall and distal walllocations are buffered for sufficient samples, and the mutual motionpattern between them is quantified, as shown in FIG. 5 . This motionpattern is inspected by comparing the expected physiologicalcharacteristic motion pattern of the arterial walls. The tracing of thewalls is continued until the inspected motion concurs with the expectedcharacteristic motion; otherwise, the locations of the walls are againfreshly identified.

FIG. 6 is a set of intermediate-stage signal graphs 600 illustrates thefrequency domain method to trace motion of boundaries of a vessel in abody using the vascular-dynamics-monitoring device 100, in accordancewith various embodiments of the present disclosure.

The locations of vessel wall boundaries (proximal and distal walllocations) identified via a suitable manual or automated method act asthe initial reference locations to trace the wall dynamics and motion(or vibrations) of vessel walls. Initially, a window with thedynamically allocated size is used to extract the proximal and distalwall echo regions constituting a sufficient number of samples (step 310and step 302). Hilbert transform operation is applied on these proximaland distal wall echo regions of the F^(th) and (F−1)^(th) frame whichyields their respective quadrature-phase counterpart. By adding theregions from the original frames (F and (F−1)) with their quadratureversions, G and (G−1), respectively single-sideband (SSB) signals aregenerated as shown in FIG. 6 .

The obtained phase is now constrained to the principle values, i.e., πto π. Further, an unwrap operation is performed to the phase by addingmultiples of ±2π whenever a jump in phase is greater than π, so as tobring it to a magnitude smaller than π. This unwrapped phase is linearwith a few breakpoints or knots in the linear trend, corresponding tothe boundaries of echo arising from each tissue interface along theultrasound scan line as shown in FIG. 6 . Identification of thelocations of these breakpoints is performed using a unidirectionalsignal derived from the first-time derivative of the unwrapped phasewaveforms. More specifically, the unidirectional signal is obtained bysubtracting the first-time derivative of the unwrapped phase with itsmean and then performing a modulus operation This procedure delineatesvarious echoes from different tissue interfaces in the extracted regionsof the proximal wall and the distal wall. Further, the locations ofinterest, such as the locations corresponding to the lumen-intima andmedia-adventitia, are identified as shown in FIG. 6 .

The interfaces of lumen-intima and media-adventitia are located from thepool of all the identified echo boundaries of the extracted region, asfollows. Envelopes are first constructed for the proximal and distalwall region extracts using a suitable method. One method is to use theSSB signals of the regions, where the envelope can be estimated as themagnitude of the complex-valued elements. An over smoothened version ofthis envelope is obtained, and its peak is identified. The location ofthe obtained peak (LP) for the respective regions represent the locationat which maximum energy of the extracted regions are concentrated.Further, the two strong echoes that are present to either side of thispeak are the echoes formed due to lumen-intima and media-adventitiainterfaces. In the case of a proximal wall, the echo on the right sideof LP is identified as the echo originated from the intima layer, andthe echo on the left side of LP as the echo originated from theadventitia layer. Similarly, for distal wall region, the echoimmediately to the left of the LP is identified as the echo originatedfrom the intima layer, and echo on the right side of LP as the echooriginated from the adventitia layer.

Amongst all the echo boundaries previously identified for the proximalwall region, the leading boundary location of the intima echo isdesignated as the lumen-intima interface (LI_(PROX)), and the trailingboundary of the adventitia echo is designated as the media-adventitiainterface (MA_(PROX)) Also, amongst all the echo boundaries previouslyidentified for the distal wall region, the leading boundary location ofthe intima echo is designated as the lumen-intima interface (LI_(DIS)),and the leading boundary of the adventitia echo is designated as themedia-adventitia interface (MA_(DIS)). These interfaces are identifiedfor the Fth and (F−1)th frames. The difference in the LI_(PROX) from thetwo frames and in the MA_(PROX) from the two frames are averaged toyield the proximal wall shift. A similar approach is adopted to producethe distal wall shift, as shown in FIG. 6 .

Shifts corresponding to the Fth frame are added to the previouslyaccumulated shifts till (F−1)th frame. If the tracing has just started,this previously accumulated shift is initialised with zero. Thisprocedure, therefore, traces the shifts in the echoes continuously withevery new incoming frame. The exact locations of the wall in the currentframe are computed by adding the current accumulated shifts with theinitially identified wall locations. These exact locations assist inshifting of the window centre that extracts the proximal and distal wallregions in the consecutive frames. The difference between the traces ofaccumulated shifts in the proximal and distal walls provide distensiontrace. Likewise, the difference between the traces of exact locations ofthe proximal and distal walls in the frame produces the diameterwaveform. The proximal wall and distal wall locations are buffered forevery N sufficient samples, and the mutual motion pattern between themis quantified. This motion pattern is inspected by comparing thephysiological characteristic motion pattern of the arterial walls. Thetracing of the walls is continued until the inspected motion concurswith the expected characteristic motion as shown in FIG. 6 . Otherwise,the locations of the walls are again freshly identified.

The foregoing descriptions of specific embodiments of the presenttechnology have been presented for purposes of illustration anddescription. They are not intended to be exhaustive or to limit thepresent technology to the precise forms disclosed, and obviously manymodifications and variations are possible in light of the aboveteaching. The embodiments were chosen and described in order to bestexplain the principles of the present technology and its practicalapplication, to thereby enable others skilled in the art to best utilizethe present technology and various embodiments with variousmodifications as are suited to the particular use contemplated. It isunderstood that various omissions and substitutions of equivalents arecontemplated as circumstance may suggest or render expedient, but suchare intended to cover the application or implementation withoutdeparting from the spirit or scope of the claims of the presenttechnology.

While several possible embodiments of the invention have been describedabove and illustrated in some cases, it should be interpreted andunderstood as to have been presented only by way of illustration andexample, but not by limitation. Thus, the breadth and scope of apreferred embodiment should not be limited by any of the above-describedexemplary embodiments.

We claim:
 1. A method for tracing motion of blood vessel boundaries in ahuman body, the method comprising: receiving, by anvascular-dynamics-monitoring device (100), a plurality of ultrasoundsignals from the blood vessel; continuously extracting, by thevascular-dynamics-monitoring device (100), at least two consecutiveultrasound frames from the plurality of ultrasound signals; identifying,by the vascular-dynamics-monitoring device (100), a proximal wall and adistal wall of the blood vessel from the at least two consecutiveultrasound frames from the plurality of ultrasound signals; dynamicallyextracting, by the vascular-dynamics-monitoring device (100), at leastone echo region of the proximal wall and the distal wall of the bloodvessels; comparing, by the vascular-dynamics-monitoring device (100),the at least one echo region from each of the at least two consecutiveultrasound frames; determining, by the vascular-dynamics-monitoringdevice (100), a shift of the at least one echo region on each of theproximal wall and the distal wall based on the comparison; and tracing,by the vascular-dynamics-monitoring device (100), the motion of theproximal wall and the distal wall based on the continuously determinedmotion shift of the at least one echo region on each of the proximalwall and the distal wall.
 2. The method as claimed in claim 1, furthercomprising continuing tracing by the vascular-dynamics-monitoring device(100) the motion of the proximal wall and the distal wall until thetracing concurs with an expected motion of the proximal wall and thedistal wall.
 3. The method as claimed in claim 1, wherein the ultrasoundframe is a digitized data frame of the ultrasound echo signal with afinite number of samples.
 4. The method as claimed in claim 1, whereinthe proximal wall and the distal wall of the blood vessel move inopposite directions.
 5. The method as claimed in claim 1, whereindynamically extracting the at least one echo region on each of theproximal wall and the distal wall comprises placing at least two windowswith dynamically allocated sizes around each of the plurality ofultrasound signals received from the identified proximal wall and theidentified distal wall.
 6. The method as claimed in claim 1, whereincomparing the at least one echo region of each of the proximal wall andthe distal wall of each of the at least two consecutive ultrasoundframes is to determine at least one delay waveform between the each ofthe regions or a first time-derivative of unwrapped analytic phasewaveforms of the each of the proximal wall echo region and the distalwall region.
 7. The method as claimed in claim 6, wherein determiningthe delay waveform between each of the proximal wall echo region and thedistal wall region comprises: comparing samples of the each echo regionsof the proximal wall and the distal wall to determine an alignmentdissimilarity between the echo regions; generating a two-dimensionalalignment error matrix based on the alignment dissimilarity between theecho regions; translating the two-dimensional error matrix to anaccumulated distance matrix; determining local minimum accumulatederrors and global minimum accumulated errors from the accumulateddistance matrix; and generating the delay waveform based on thedetermined local minimum accumulated errors and the global minimumaccumulated errors.
 8. The method as claimed in claim 6, whereindetermining the first time-derivative of unwrapped phase change waveformbetween the at least two consecutive ultrasound frames comprises:determining a quadrature phase counterpart corresponding to each of theat least one echo region of each of the at least two ultrasound framesby applying Hilbert transform on each of the at least one echo region ofthe each of the at least two ultrasound frames; generating a singlesideband (SSB) signal corresponding to each of the at least one echoregion of each of the at least two ultrasound frames by adding the eachof the echo regions to the corresponding quadrature phase counterpart;constructing continuous phase waveforms of each of the echo regions byperforming a tangent inverse operation on the SSB signal correspondingto each of the at least two ultrasound frames; and constructing theunwrapped phase waveforms by performing a time-domain unwrappingoperation, differentiating the unwrapped phase waveforms of each of theat least one echo region of each of the proximal wall and the distalwall with respect to time once.
 9. The method as claimed in claim 1,wherein determining the shift comprises determining at least oneextremum of the delay waveform or at least two extrema of interest ofthe first time-derivative of the unwrapped analytic phase waveforms,where the at least one extremum of the delay waveform or the averageshift in the at least two extrema of interest of the firsttime-derivative of the unwrapped analytic phase waveforms.
 10. Themethod as claimed in claim 1, wherein the ultrasound frames comprise anequal number of samples.
 11. The method as claimed in claim 1, whereinthe ultrasound frames comprise an unequal number of samples.
 12. Avascular-dynamics-monitoring device (100) for identifying boundaries ofa blood vessel in a human body, the vascular-dynamics-monitoring device(100) comprising: a memory (102) for storing ultrasound frames; a signaltransceiver (104) configured for receiving a plurality of ultrasoundecho signals from an ultrasound transducer (110), wherein the pluralityof ultrasound echo signals are transmitted to the ultrasound transducer(110) from the blood vessel; a sample extractor (106) communicativelycoupled to the signal transceiver (104) and the memory (102), configuredfor: continuously extracting at least two consecutive ultrasound framesfrom the plurality of ultrasound echo signals received from the at leastone echo region; dynamically extracting at least one echo region fromeach of the at least two ultrasound frames, and storing the at least twoconsecutive ultrasound frames and the at least one echo region in thememory (110); a controller (108) communicatively connected to the sampleextractor (106), the signal transceiver (104) and the memory (102),configured to: compare the at least one echo region of each of theproximal wall and the distal wall of each of the at least twoconsecutive ultrasound frames; determine a shift of the at least oneecho region on each of the proximal wall and the distal wall based onthe comparison; and trace the motion of the proximal wall and the distalwall based on the continuously determined motion shift of the at leastone echo region on each of the proximal wall and the distal wall. 13.The vascular-dynamics-monitoring device (100) as claimed in claim 12further comprising continuing tracing of the proximal wall and thedistal wall until the tracing concurs with an expected motion of theproximal wall and the distal wall.
 14. The vascular-dynamics-monitoringdevice (100) as claimed in claim 12, wherein an ultrasound frame is adigitized data frame of the ultrasound echo signal with a finite numberof samples.
 15. The vascular-dynamics-monitoring device (100) as claimedin claim 12, wherein the proximal wall and the distal wall of the bloodvessel of the user move in opposite directions.
 16. Thevascular-dynamics-monitoring device (100) as claimed in claim 12,wherein dynamically identifying at least one echo region on each of theproximal wall and the distal wall comprises placing at least two windowswith dynamically allocated sizes around each of the plurality ofultrasound signals received from the identified proximal wall and theidentified distal wall.
 17. The vascular-dynamics-monitoring device(100) as claimed in claim 12, wherein comparing the at least one echoregion of each of the proximal wall and the distal wall of each of theat least two consecutive ultrasound frames is to determine at least onedelay waveform between the each of the regions or first time-derivativeof unwrapped analytic phase waveforms of the each of the proximal wallecho region and the distal wall region.
 18. Thevascular-dynamics-monitoring device (100) as claimed in claim 17,wherein determining the delay waveform between the corresponding echoregions of the at least two consecutive ultrasound frames comprises:comparing samples of the echo regions to determine an alignmentdissimilarity between the echo regions; generating a two-dimensionalalignment error matrix based on the alignment dissimilarity between theecho regions; translating the two-dimensional error matrix to anaccumulated distance matrix; determining local minimum accumulatederrors and global minimum accumulated errors from the accumulateddistance matrix; and generating the delay waveform based on thedetermined local minimum accumulated errors and the global minimumaccumulated errors.
 19. The vascular-dynamics-monitoring device (100) asclaimed in claim 17, wherein determining the first derivative ofunwrapped phase change waveform between the at least two consecutiveultrasound frames comprises: determining a quadrature phase counterpartcorresponding to each of the at least one echo region of each of the atleast two ultrasound frames by applying Hilbert transform on the atleast one echo region of each of the at least two ultrasound frames;generating a single sideband (SSB) signal corresponding to each of theat least one echo region of each of the at least two ultrasound framesby adding the each of the echo regions to the corresponding quadraturephase counterpart; constructing continuous phase waveforms of each ofthe echo regions by performing a tangent inverse operation on the SSBsignal corresponding to each of the at least two ultrasound frames; andconstructing the unwrapped phase waveforms by performing a time-domainunwrapping operation, differentiating the unwrapped phase waveforms ofeach of the at least one echo region of each of the proximal wall andthe distal wall with respect to time once.
 20. Thevascular-dynamics-monitoring device (100) as claimed in claim 12,wherein determining the shift comprises determining at least oneextremum of the delay waveform or at least two extrema of interest ofthe first time-derivative of the unwrapped analytic phase waveforms,where the at least one extremum of the delay waveform or the averageshift in the at least two extrema of interest of the firsttime-derivative of the unwrapped analytic phase waveforms.
 21. Thevascular-dynamics-monitoring device (100) as claimed in claim 10,wherein the echo regions comprise an equal number of samples.
 22. Thevascular-dynamics-monitoring device (100) as claimed in claim 10,wherein the echo regions comprise an unequal number of samples.